Main
Carlos A. Haro
Data scientist with experience in economic analysis
Main focus on data visualization and supervised learning.
Education
(ITAM) Instituto Tecnológico Autónomo de México
B.S., Economics
Mexico City, Mexico
2014 - 2018
Experience
Sr. Data Scientist
Mexico’s Central Tax Administration Office
(Servicio de Administración Tributaria)
Mexico City
Jan. 2019 - present
- Development and deployment of a supervised model for classifying tax debt | R (tidyverse, ranger), Python (scikit-learn, pandas), SQL
- Designed and taught three courses for the institution’s staff training: introduction to R, basics of exploratory data analysis, building data science pipelines using Makefiles | R (tidyverse, ggplot2), GNU Make
- Designed a pipeline for automatic generation of frequent data visualization reports | R Markdown (ggplot2, shiny)
- Perform network analysis to detect tax evasion communities | R (tidyverse, visnetwork, ggraph)
- Version control of cloropleth maps for the geographical display of taxpayer’s data | R (leaflet QGis)
Jr. Data Scientist | Economic Analyst
EnergeA (Energy Sector Consulting Firm)
Mexico City
2018
- Developed a statistical model for identifying anti-competitive practices between the mid-stream natural gas providers | R
- Neighboring gas station’s competition analysis for identifying price setting mechanisms. | R
- Built a PDF scrapping pipeline of 100+ files for ownership analysis of Mexico’s natural gas industry. | R (stringr, selenium)
Miscellaneous
Hackaton challenge winner
Annual BBVA Hackaton Challenge
N/A
2019
Organizer: BBVA Bank
Challenge: Update and insert operation of a 50 million observations dataset in under 10 minutes.
Result: 95%+ accuracy of update and insert achieved in 4 minutes | Pyspark on AWS for the algorithm, RMarkdown for the report
Hackaton participant
Annual Banamex Hackaton Challenge
N/A
2019
Organizer: Banamex Bank
Challenge: Create any platform for aiding small mexican businesses (< 75,000 usd/year cash flow) flourish.
Result: Created a live dashboard service that calculated the probability of succes of a business given initial investment, number of employees, employee salary, etc. | R (shiny), Python (scikit-learn), AWS